Research Directions

Intelligent Risk Analysis Platform for Knee and Hip Joint Replacement Surgery
UpdateTime:2024-03-18 01:43

As the population ages, our healthcare system faces three main burdens of disease: cancer (chemotherapy/radiation therapy and surgical oncology), cardiovascular diseases (coronary and cardiac surgery and interventional treatments), and degenerative joint diseases (hip/knee joint replacement surgery).


To address this key/large-scale challenge with a multidisciplinary team (including the School of Medicine at the Chinese University of Hong Kong (Shenzhen), Shenzhen Municipal Big Data Research Institute, Shenzhen Institute of Artificial Intelligence and Robotics, Data Science Institute at the Chinese University of Hong Kong (Shenzhen), School of Engineering, Business School, and affiliated/teaching hospitals), we have chosen to study a common single longitudinal continuous surgery—hip/knee joint replacement surgery—combining the application of artificial intelligence and data analysis with evidence-based knowledge translation and longitudinal continuity interventions in the care of hip/knee joint surgery patients. This orthopedic surgery brings a significant burden on emergency medical resources for the elderly population, necessitating our use of artificial intelligence to determine risk prediction and prevention, surgical optimization and intervention, perioperative technology and equipment utilization, early mobilization and rehabilitation, and discharge and home care.


The team has already initiated research in the following six areas:

(1) Improving the accuracy of diagnostic tests (laboratory testing, AI medical imaging) and developing intelligent algorithms for assisting hip/knee joint surgeries and patient referrals;

(2) Designing better protocols to improve the quality, safety, and cost of perioperative care (medication, technology, anesthesia techniques, surgical methods and equipment, pain management, rehabilitation), and exploring business models for precision medical care in hip/knee joint surgeries;

(3) Promoting the use of AI home monitoring for discharged and postoperative patients, thus shortening hospital stays and reducing the cost of hip/knee joint surgeries. Establishing R&D partnerships with the AI industry to jointly develop AI-based diagnostic and monitoring devices;

(4) Enhancing community management (social workers, nurses, physiotherapists) to improve patient satisfaction and prevent and improve the health of those at risk of hip/knee joint diseases, such as reducing obesity and advocating for healthy living in the community;

(5) Collaborating with industry to develop resources and equipment needed during the care process of hip/knee joint surgeries, such as joint bioprostheses with antibacterial properties, and postoperative home monitoring and response devices;

(6) Developing risk prediction algorithms and precision treatment for hip/knee joint diseases.


The collaborative team's research outcomes will facilitate the implementation of AI-based solutions in hip/knee joint surgeries in Luohu and the Greater Bay Area hospitals and promote related health policies nationwide.

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